update model card README.md
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.ipynb_checkpoints/fine-tune-whisper-streaming-checkpoint.ipynb
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README.md
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---
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language:
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- et
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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- name: Whisper Medium et
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: ERR2020, Common Voice 11.0, FLEURS
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type: mozilla-foundation/common_voice_11_0
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config: et
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split: test
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args: et
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metrics:
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- name: Wer
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type: wer
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value: 29.720322799236126
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper Medium et
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the ERR2020, Common Voice 11.0, FLEURS dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4288
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- Wer: 29.7203
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
|
55 |
+
|
56 |
+
The following hyperparameters were used during training:
|
57 |
+
- learning_rate: 1e-06
|
58 |
+
- train_batch_size: 32
|
59 |
+
- eval_batch_size: 16
|
60 |
+
- seed: 42
|
61 |
+
- gradient_accumulation_steps: 2
|
62 |
+
- total_train_batch_size: 64
|
63 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
64 |
+
- lr_scheduler_type: linear
|
65 |
+
- lr_scheduler_warmup_steps: 500
|
66 |
+
- training_steps: 5000
|
67 |
+
- mixed_precision_training: Native AMP
|
68 |
+
|
69 |
+
### Training results
|
70 |
+
|
71 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
72 |
+
|:-------------:|:-----:|:----:|:---------------:|:-------:|
|
73 |
+
| 0.4018 | 0.1 | 500 | 0.5518 | 39.3951 |
|
74 |
+
| 0.2654 | 0.2 | 1000 | 0.4611 | 34.3929 |
|
75 |
+
| 0.2121 | 0.3 | 1500 | 0.4346 | 32.0582 |
|
76 |
+
| 0.1752 | 0.4 | 2000 | 0.4247 | 31.1926 |
|
77 |
+
| 0.1337 | 0.5 | 2500 | 0.4216 | 30.3364 |
|
78 |
+
| 0.1281 | 0.6 | 3000 | 0.4219 | 30.0745 |
|
79 |
+
| 0.1127 | 0.7 | 3500 | 0.4252 | 29.7388 |
|
80 |
+
| 0.1254 | 0.8 | 4000 | 0.4276 | 29.8928 |
|
81 |
+
| 0.1035 | 0.9 | 4500 | 0.4292 | 29.7634 |
|
82 |
+
| 0.1114 | 1.0 | 5000 | 0.4288 | 29.7203 |
|
83 |
+
|
84 |
+
|
85 |
+
### Framework versions
|
86 |
+
|
87 |
+
- Transformers 4.26.0.dev0
|
88 |
+
- Pytorch 1.13.0+cu117
|
89 |
+
- Datasets 2.7.1.dev0
|
90 |
+
- Tokenizers 0.13.2
|
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